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TIL: Caveman – Context Compression and File Bundling for AI Workflows

Repository: github.com/juliusbrussee/caveman

Topic: Context Engineering & Developer Tooling

Came across Caveman, a lightweight CLI utility designed to streamline how source code and project context are fed into LLMs and coding assistants.

Key Takeaways & Production Utility:

  • Context Efficiency: It bundles relevant directory files into clean, structured context payloads, reducing prompt noise and token overhead.

  • Developer Workflow: Helps bridges the gap when feeding targeted codebase snippets to CLI tools (like Claude Code) or API scripts without manually copy-pasting files.

  • Use Case: Ideal for rapid repository analysis and prepping context windows for LLM code generation tasks.

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  • TIL: Unified Memory Bandwidth is the Real Bottleneck for Local LLMs
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  • TIL: RTK (Rust Token Killer) – 80% Token Reduction for Agent CLI Logs
  • Context Engineering
  • TIL: Caveman – Lightweight Context & File Packing for LLMs

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JLVBCoop

Full Stack & AI Engineer with 15+ years of experience. Building robust software with Java, React, and modern AI workflows.

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Entradas recientes

  • TIL: Unified Memory Bandwidth is the Real Bottleneck for Local LLMs
  • TIL: Knowledge Graph Retrieval – Stop Codebase Re-Reads with Graphify & CodeGraph
  • TIL: RTK (Rust Token Killer) – 80% Token Reduction for Agent CLI Logs
  • Context Engineering
  • TIL: Caveman – Lightweight Context & File Packing for LLMs
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